A Water Relaxation Atlas for Age- and Region-Specific Metabolite Concentration Correction at 3 T

Metabolite concentration estimates from magnetic resonance spectroscopy (MRS) are typically quantified using water referencing, correcting for relaxation-time differences between metabolites and water. One common approach is to correct the reference signal for differential relaxation within three tissue compartments (gray matter, white matter, and cerebrospinal fluid) using fixed literature values. However, water relaxation times (T₁ and T₂) vary between brain locations and with age. MRS studies, even those measuring metabolite levels across the lifespan, often ignore these effects, because of a lack of reference data. The purpose of this study is to develop a water relaxometry atlas and to integrate location- and age-appropriate relaxation values into the MRS analysis workflow. One hundred one volunteers (51 men, 50 women; ~10 male, and 10 female participants per decade from the 20s to 60s) were recruited. T₁-weighted MPRAGE images ((1-mm)³ isotropic resolution) were acquired. Whole-brain water T₁ and T₂ measurements were made with DESPOT ((1.4 mm)³ isotropic resolution) at 3T. T₁ and T₂ maps were registered to the JHU MNI-SS/EVE atlas using affine and LDDMM transformation. The atlas's 268 parcels were reduced to 130 by combining homologous parcels. Mean T₁ and T₂ values were calculated for each parcel in each subject. Linear models of T₁ and T₂ as functions of age were computed, using age - 30 as the predictor. Reference atlases of "age-30-intercept" and age-slope for T₁ and T₂ were generated. The atlas-based workflow was integrated into Osprey, which co-registers MRS voxels to the atlas and calculates location- and age-appropriate water relaxation parameters for quantification. The water relaxation aging atlas revealed significant regional and tissue differences in water relaxation behavior across adulthood. Using location- and subject-appropriate reference values in the MRS analysis workflow removes a current methodological limitation and is expected to reduce quantification biases associated with water-referenced tissue correction, especially for studies of aging.